{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "34681448-df13-4b93-abf5-56ae4f75966e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "生成订单条数： 13916\n",
      "\n",
      "校验通过：汇总月度销量与目标表完全一致！\n",
      "      年份   月份    销量\n",
      "0   2021   5月   146\n",
      "1   2021   6月   198\n",
      "2   2021   7月   296\n",
      "3   2021   8月   412\n",
      "4   2021   9月   506\n",
      "5   2021  10月   615\n",
      "6   2021  11月   789\n",
      "7   2021  12月  1021\n",
      "8   2022   1月  3782\n",
      "9   2022   2月  3215\n",
      "10  2022   3月  2936\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import random\n",
    "from datetime import datetime, timedelta\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from faker import Faker\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Rectangle\n",
    "\n",
    "# ================== 0. 全局设置 ==================\n",
    "fake = Faker(\"zh_CN\")\n",
    "random.seed(42)\n",
    "Faker.seed(42)\n",
    "\n",
    "# 中文字体（根据自己电脑情况调整）\n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\", \"Microsoft YaHei\", \"SimSun\"]\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False\n",
    "\n",
    "# ================== 1. 目标月度销量表（来自 Excel） ==================\n",
    "target_data = [\n",
    "    (2021, \"5月\", 146),\n",
    "    (2021, \"6月\", 198),\n",
    "    (2021, \"7月\", 296),\n",
    "    (2021, \"8月\", 412),\n",
    "    (2021, \"9月\", 506),\n",
    "    (2021, \"10月\", 615),\n",
    "    (2021, \"11月\", 789),\n",
    "    (2021, \"12月\", 1021),\n",
    "    (2022, \"1月\", 3782),\n",
    "    (2022, \"2月\", 3215),\n",
    "    (2022, \"3月\", 2936),\n",
    "]\n",
    "summary_target = pd.DataFrame(target_data, columns=[\"年份\", \"月份\", \"销量\"])\n",
    "\n",
    "# 为后面排序准备一个“月份数字”\n",
    "summary_target[\"月份数字\"] = summary_target[\"月份\"].str.replace(\"月\", \"\").astype(int)\n",
    "summary_target = summary_target.sort_values([\"年份\", \"月份数字\"])[[\"年份\", \"月份\", \"销量\"]]\n",
    "\n",
    "# ================== 2. 基于 erp_order Schema 生成模拟订单数据 ==================\n",
    "records = []\n",
    "order_id = 1\n",
    "\n",
    "for year, month_label, sales in target_data:\n",
    "    month = int(month_label.replace(\"月\", \"\"))\n",
    "\n",
    "    # 月份起止时间\n",
    "    start = datetime(year, month, 1, 0, 0, 0)\n",
    "    if month == 12:\n",
    "        end = datetime(year + 1, 1, 1) - timedelta(seconds=1)\n",
    "    else:\n",
    "        end = datetime(year, month + 1, 1) - timedelta(seconds=1)\n",
    "\n",
    "    # 让“销量 = 订单数量”，这里 quantity=1，循环 sales 次\n",
    "    for _ in range(sales):\n",
    "        order_time = fake.date_time_between_dates(datetime_start=start,\n",
    "                                                  datetime_end=end)\n",
    "        payment_date = order_time + timedelta(hours=random.randint(0, 48))\n",
    "        shipping_date = payment_date + timedelta(days=random.randint(0, 5))\n",
    "\n",
    "        quantity = 1\n",
    "        unit_price = round(random.uniform(50, 400), 2)\n",
    "        product_amount = round(unit_price * quantity, 2)\n",
    "        original_price = round(unit_price + random.uniform(0, 100), 2)\n",
    "\n",
    "        refund_status = random.choice([\"未申请退款\", \"成功退款\", \"退款中\"])\n",
    "        actual_refund_quantity = 1 if refund_status == \"成功退款\" else 0\n",
    "\n",
    "        record = {\n",
    "            \"id\": order_id,\n",
    "            \"internal_order_number\": fake.uuid4(),\n",
    "            \"online_order_number\": fake.uuid4(),\n",
    "            \"store_name\": random.choice([\"旗舰店A\", \"旗舰店B\", \"官方自营店\"]),\n",
    "            \"full_channel_user_id\": fake.uuid4().replace(\"-\", \"\"),\n",
    "            \"shipping_date\": shipping_date,\n",
    "            \"payment_date\": payment_date,\n",
    "            \"payable_amount\": product_amount,\n",
    "            \"paid_amount\": product_amount,\n",
    "            \"status\": random.choice([\"已发货\", \"已完成\", \"待发货\"]),\n",
    "            \"consignee\": fake.name(),\n",
    "            \"spu\": f\"SPU{random.randint(1000, 9999)}\",\n",
    "            \"order_time\": order_time,\n",
    "            \"province\": fake.province(),\n",
    "            \"city\": fake.city_name(),\n",
    "            \"platform\": random.choice([\"天猫\", \"京东\", \"抖音\"]),\n",
    "            \"sub_order_number\": fake.uuid4().split(\"-\")[0],\n",
    "            \"online_sub_order_number\": fake.uuid4().split(\"-\")[0],\n",
    "            \"original_online_order_number\": fake.uuid4(),\n",
    "            \"sku\": f\"SKU{random.randint(100000, 999999)}\",\n",
    "            \"quantity\": quantity,\n",
    "            \"unit_price\": unit_price,\n",
    "            \"product_name\": random.choice([\"保湿水\", \"精华液\", \"面霜\", \"洁面乳\"]),\n",
    "            \"color_and_spec\": random.choice([\"50ml\", \"100ml\", \"150ml\"]),\n",
    "            \"product_amount\": product_amount,\n",
    "            \"original_price\": original_price,\n",
    "            \"is_gift\": random.choice([\"是\", \"否\"]),\n",
    "            \"sub_order_status\": random.choice([\"正常\", \"关闭\"]),\n",
    "            \"refund_status\": refund_status,\n",
    "            \"registered_quantity\": quantity,\n",
    "            \"actual_refund_quantity\": actual_refund_quantity,\n",
    "        }\n",
    "        records.append(record)\n",
    "        order_id += 1\n",
    "\n",
    "df_erp = pd.DataFrame(records)\n",
    "print(\"生成订单条数：\", len(df_erp))  # 应该是 13916 ≥ 1000\n",
    "\n",
    "# ================== 3. 从订单数据汇总出月度销量，并与目标表严格对齐 ==================\n",
    "df_erp[\"year\"] = df_erp[\"order_time\"].dt.year\n",
    "df_erp[\"month_num\"] = df_erp[\"order_time\"].dt.month\n",
    "\n",
    "agg_df = (\n",
    "    df_erp\n",
    "    .groupby([\"year\", \"month_num\"])[\"quantity\"]\n",
    "    .sum()\n",
    "    .reset_index()\n",
    "    .rename(columns={\"year\": \"年份\", \"month_num\": \"月份数字\", \"quantity\": \"销量\"})\n",
    ")\n",
    "\n",
    "agg_df = agg_df.sort_values([\"年份\", \"月份数字\"])\n",
    "agg_df[\"月份\"] = agg_df[\"月份数字\"].astype(str) + \"月\"\n",
    "agg_df = agg_df[[\"年份\", \"月份\", \"销量\"]]\n",
    "\n",
    "# ====== 关键修改：统一“年份”列的数据类型，避免 int32 / int64 不一致 ======\n",
    "agg_df[\"年份\"] = agg_df[\"年份\"].astype(\"int64\")\n",
    "summary_target[\"年份\"] = summary_target[\"年份\"].astype(\"int64\")\n",
    "\n",
    "# 校验汇总结果与目标表完全一致（不一致会抛异常）\n",
    "pd.testing.assert_frame_equal(\n",
    "    agg_df.reset_index(drop=True),\n",
    "    summary_target.reset_index(drop=True)\n",
    ")\n",
    "print(\"\\n校验通过：汇总月度销量与目标表完全一致！\")\n",
    "print(agg_df)\n",
    "\n",
    "# ================== 4. 画出类似 Excel 模板的折线图 ==================\n",
    "fig, ax = plt.subplots(figsize=(12, 7))\n",
    "fig.patch.set_facecolor(\"#151c3b\")     # 整个画布背景\n",
    "ax.set_facecolor(\"#151c3b\")           # 坐标区背景\n",
    "\n",
    "# X 轴用位置索引，标签用“月份”\n",
    "x = np.arange(len(agg_df))\n",
    "y = agg_df[\"销量\"].values\n",
    "\n",
    "ax.plot(x, y, linewidth=2.5, color=\"#ff7f50\")\n",
    "\n",
    "ax.set_xticks(x)\n",
    "ax.set_xticklabels(agg_df[\"月份\"], color=\"#ffffff\", fontsize=11)\n",
    "\n",
    "ax.set_ylim(0, 4000)\n",
    "ax.set_yticks([0, 1000, 2000, 3000, 4000])\n",
    "ax.set_yticklabels([\"0\", \"1,000\", \"2,000\", \"3,000\", \"4,000\"],\n",
    "                   color=\"#ff7f50\", fontsize=11)\n",
    "\n",
    "# 坐标轴 & 刻度样式\n",
    "for spine in [\"top\", \"right\", \"left\", \"bottom\"]:\n",
    "    ax.spines[spine].set_color(\"#ffffff\")\n",
    "    ax.spines[spine].set_linewidth(0.8)\n",
    "\n",
    "ax.tick_params(axis=\"x\", colors=\"#ffffff\")\n",
    "ax.tick_params(axis=\"y\", colors=\"#ff7f50\")\n",
    "\n",
    "# 标题与副标题\n",
    "ax.set_title(\"化妆品品类月度销量走势\",\n",
    "             fontsize=24, color=\"white\", loc=\"left\", pad=20)\n",
    "ax.text(0, 1.00,\n",
    "        \"2022年销量迅速增加，1月最高，销量达到3782\",\n",
    "        transform=ax.transAxes,\n",
    "        fontsize=14, color=\"white\",\n",
    "        ha=\"left\", va=\"bottom\")\n",
    "\n",
    "# 高亮 2022 年 1 月峰值\n",
    "peak_pos = np.where((agg_df[\"年份\"] == 2022) & (agg_df[\"月份\"] == \"1月\"))[0][0]\n",
    "peak_y = agg_df.iloc[peak_pos][\"销量\"]\n",
    "\n",
    "# 竖直虚线\n",
    "ax.axvline(peak_pos, ymax=peak_y / 4000,\n",
    "           color=\"#ff7f50\", linestyle=\"--\", linewidth=1.5)\n",
    "# 数值标注\n",
    "ax.text(peak_pos, peak_y + 200, str(peak_y),\n",
    "        color=\"white\", fontsize=12, ha=\"center\", va=\"bottom\")\n",
    "\n",
    "# ================== 底部年份色块 ==================\n",
    "transform = ax.get_xaxis_transform()  # x 用数据坐标，y 用轴坐标\n",
    "\n",
    "# 2021 色块（前 8 个月：5~12 月）\n",
    "ax.add_patch(\n",
    "    Rectangle(\n",
    "        (-0.4, -0.18),\n",
    "        8.0,\n",
    "        0.08,\n",
    "        transform=transform,\n",
    "        clip_on=False,\n",
    "        color=\"#26c6da\",\n",
    "    )\n",
    ")\n",
    "ax.text(3.5, -0.14, \"2021\",\n",
    "        transform=transform,\n",
    "        ha=\"center\", va=\"center\",\n",
    "        color=\"white\", fontsize=12)\n",
    "\n",
    "# 2022 色块（后 3 个月：1~3 月）\n",
    "ax.add_patch(\n",
    "    Rectangle(\n",
    "        (7.6, -0.18),\n",
    "        3.0,\n",
    "        0.08,\n",
    "        transform=transform,\n",
    "        clip_on=False,\n",
    "        color=\"#ffca28\",\n",
    "    )\n",
    ")\n",
    "ax.text(9.1, -0.14, \"2022\",\n",
    "        transform=transform,\n",
    "        ha=\"center\", va=\"center\",\n",
    "        color=\"white\", fontsize=12)\n",
    "\n",
    "plt.subplots_adjust(bottom=0.22)\n",
    "\n",
    "# 数据来源说明\n",
    "fig.text(0.05, 0.03,\n",
    "         \"*注：数据来源于公司销售系统，统计日期截至2022.03.31\",\n",
    "         color=\"white\", fontsize=10)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "961e27bb-a834-46af-b35e-af7e4e4cebec",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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